ABSTRACT In sponsored search advertising, advertisers need to make a series of keyword decisions. Grouping these keywords to form several adgroups within a campaign is a challenging task because of the highly uncertain environment of search advertising. This paper proposes a stochastic programming model for keywords grouping, taking click-through rate and conversion rate as random variables, with consideration of budget constraints and advertisers’ risk-tolerance. A branch-and-bound algorithm is developed to solve our model. Furthermore, we conduct computational experiments to evaluate the effectiveness of our model and solution, with two real-world data sets collected from reports and logs of search advertising campaigns. Experimental results illustrated that our keywords grouping approach outperforms five baselines, and it can approximately and steadily approach the optimal solution. This research generates several interesting findings that illuminate critical managerial insights for advertisers in sponsored search advertising. First, keywords grouping does matter for advertisers, especially with a large number of keywords. Second, in keywords grouping decisions, the marginal profit does not necessarily show the marginal diminishing phenomenon as the budget increases. Therefore, advertisers should try to increase their budget in keywords grouping decisions to garner additional profit. Third, the optimal keywords grouping solution is the result of a multifaceted trade-off among various advertising factors. In particular, assigning more keywords into adgroups or having a larger budget will not definitely lead to higher profits. This study suggests a warning for advertisers: It is not wise to use the number of keywords as a single criterion for keywords grouping decisions.

中文翻译：

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不确定环境下赞助搜索广告中的最佳关键词分组

摘要 在赞助搜索广告中，广告商需要做出一系列关键词决策。由于搜索广告环境的高度不确定性，将这些关键字分组以形成广告系列中的多个广告组是一项具有挑战性的任务。本文提出了一种关键词分组的随机规划模型，以点击率和转化率为随机变量，同时考虑预算约束和广告商的风险承受能力。开发了一种分支定界算法来解决我们的模型。此外，我们使用从搜索广告活动的报告和日志中收集的两个真实数据集进行计算实验来评估我们的模型和解决方案的有效性。实验结果表明，我们的关键字分组方法优于五个基线，并且可以近似稳定地逼近最优解。这项研究产生了几个有趣的发现，这些发现阐明了赞助搜索广告中广告商的关键管理见解。首先，关键字分组对广告商来说很重要，尤其是在关键字数量众多的情况下。其次，在关键词分组决策中，边际利润不一定随着预算的增加而呈现边际递减的现象。因此，广告商应尝试在关键字分组决策中增加预算以获取额外利润。第三，最优关键词分组方案是各种广告因素多方面权衡的结果。尤其是，将更多的关键字分配到广告组中或拥有更大的预算并不一定会带来更高的利润。